Title of article :
Improved Automatic Clustering Using a Multi-Objective Evolutionary Algorithm with New Validity Measure and Application to Credit Scoring
Author/Authors :
Mohammadi Rad, Majid 1 Department of Computer and Information Technology Engineering - Qazvin Branch - Islamic Azad University , Afzali, Mahdi Faculty of Computer Engineering - Islamic Azad University - Zanjan Branch
Abstract :
In data mining, clustering is one of the important issues for separation
and classification with groups like unsupervised data. In this
paper, an attempt has been made to improve and optimize the application
of clustering heuristic methods such as Genetic, PSO algorithm,
Artificial bee colony algorithm, Harmony Search algorithm and Differential
Evolution on the unlabeled data of an Iranian bank with the
credit scoring approach. A survey was also used to measure the clustering
validity index which resulted in a new validity index. Finally,
the results were compared to identify the best algorithm and validity
measure (Das & Konar, 2009).
Keywords :
Clustering , Data mining , Evolution Algorithm , Credit Score , Clustering Validity Measure
Journal title :
Astroparticle Physics
